| User | Lucky_n00b |
| Upload Date | March 14 2025 10:17 PM |
| Views | 16 |
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 9 285H |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. Prestige 16 AI Evo B2HMG |
| Motherboard | Micro-Star International Co., Ltd. MS-15A1 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 9 285H |
| Topology | 1 Processor, 16 Cores |
| Identifier | GenuineIntel Family 6 Model 197 Stepping 2 |
| Base Frequency | 2.90 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2832
526.6 IPS |
|
|
Image Classification (HP)
|
100% |
1236
229.9 IPS |
|
|
Image Classification (Q)
|
100% |
6149
1.14 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3099
50.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
1895
30.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
6487
105.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
6634
7.74 IPS |
|
|
Pose Estimation (HP)
|
100% |
6252
7.30 IPS |
|
|
Pose Estimation (Q)
|
96% |
23614
27.7 IPS |
|
|
Object Detection (SP)
|
100% |
2301
182.5 IPS |
|
|
Object Detection (HP)
|
100% |
1551
123.0 IPS |
|
|
Object Detection (Q)
|
88% |
6616
530.4 IPS |
|
|
Face Detection (SP)
|
100% |
7550
89.7 IPS |
|
|
Face Detection (HP)
|
100% |
4240
50.4 IPS |
|
|
Face Detection (Q)
|
100% |
15044
178.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
6862
52.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
5558
42.8 IPS |
|
|
Depth Estimation (Q)
|
89% |
19540
151.9 IPS |
|
|
Style Transfer (SP)
|
100% |
17920
23.0 IPS |
|
|
Style Transfer (HP)
|
100% |
17936
23.1 IPS |
|
|
Style Transfer (Q)
|
98% |
61002
78.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3410
125.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3710
137.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
11695
433.1 IPS |
|
|
Text Classification (SP)
|
100% |
2702
3.61 KIPS |
|
|
Text Classification (HP)
|
100% |
2321
3.10 KIPS |
|
|
Text Classification (Q)
|
92% |
4126
5.54 KIPS |
|
|
Machine Translation (SP)
|
100% |
2118
36.5 IPS |
|
|
Machine Translation (HP)
|
100% |
2155
37.1 IPS |
|
|
Machine Translation (Q)
|
100% |
2115
36.4 IPS |